Holtzman: General interests ● Stellar populations – Solar neighborhood star formation history – Local group dwarf star formation histories – M33 star formation history – Galactic bulge star formation history ● Galaxies – Origin of bulges – Global properties of disks – Galaxy velocity function ● Observational cosmology – Type Ia supernovae as distance indicators: SDSS-II supernova survey ● Telescopes and instrumentation – 1m operations / science – APO instrument scientist – WFC3 science oversight committee member ● Future? – SDSS-III: APOGEE and MARVELS

High resolution spectroscopy of solar neighborhood subgiants: toward high accuracy abundances? Jon Holtzman Katia Cunha (NOAO) Verne Smith (NOAO) Pey-Lian Lim Ryan Hamilton

Motivation ● Want to understand assembly of disk galaxies ● Star formation history: – History of star formation rate – History of chemical abundances – History of IMF – How important is dynamical mixing? ● Hipparcos provides distances to stars within a few hundred parsecs of the Sun – Little extinction in this region – “field” color-magnitude diagram can be constructed

Hipparcos CMD ● Clear spread of ages ● Oldest ages difficult to determine because iscochrones are tightly spaced, and depend on metallicity ● Subgiants offer the greatest leverage on stellar ages

Solar neighborhood SFH ● Solar neighborhood SFH has been determined from – CMD fitting (red: Hernandez, Valls-Gabaud, & Gilmore 2000); also Paust (2002) – Chromospheric age determination (black: Rocha- Pinto et al. 2000) ● Structure has been claimed, but is this robust? ● No strong evidence of exponentially declining SFR!

Galactic age-metallicity relation ● Naively, expect younger stars to be more metal-rich than older ones ● Only appears to be true for younger stars in solar neighborhood; significant metallicity spread at all ages ● Both ages and metallicities do have significant uncertainties, but not large enough to explain the scatter Feltzing et al. (2001)

Solar neighborhood chemistry ● Element abundance ratios change with overall abundance – Reflects different nucleosynthetic processes for different elements, e.g. ● Alpha elements ● Fe-peak elements ● S-process elements ● R-process elements ● Halo, and also thick disk (as determined kinematically), has distinct chemical signature from thin disk – Standard explanation: shorter formation timescale Bensby et al 2005

Chemical tagging ● Freeman & Bland-Hawthorn (2002) suggest disk might be decomposed into discrete star formation events (e.g. Stellar clusters/associations) – Positional &/or kinematic information about these is lost through disruption and dynamical processes – Chemical information might still be able to uniquely identify them ● De Silva, Freeman et al have been investigating open clusters, and suggest that stars within clusters have consistent chemical signatures that vary from cluster to cluster

Project goals ● Use Hipparcos HR diagram to study solar neighborhood SFH ● Measure detailed abundances of subgiant subsample to constrain SFH ● Look for chemical signatures in detailed abundances – Attempt to understand how to obtain most accurate abundances ● Key new feature: stars with well-determined ages ● Investigation of automated analysis

Sample ● All Hipparcos stars with – d<100pc – 1 < M_V < 4, in well-defined color range – Declination > -10 – Not known binary or high-amplitude variable ● Total sample: 177 stars ● Obtain echelle spectra at high S/N (>200) – Multiple runs from , all complete

APO Echelle spectra ● Spectra obtained over past 6 years at APO 3.5m telescope ● ARC echelle – Permanently mounted on NA1 port – R~32000 – Entire optical window in single spectrum – Integrations generally 5-30 minutes

Equivalent width measurements ● Automated procedure to fit/deblend lines

Abundance determinations ● Equivalent widths depend on – Abundance – Temperature – Surface gravity – “Microturbulence” – Structure of stellar atmosphere – Atomic parameters (“gf” values, excitation levels)

Stellar parameter derivation ● Traditionally, two techniques for stellar parameter derivation – Spectroscopic ● Determine Teff by requiring that all lines of given element/ionization, but at different excitation potentials, give same abundance (e.g. FeI) ● Determine log g by requiring abundance from different ionization states to be the same (e.g. FeI/FeII) ● Determine “microturbulence” by requiring lines of different reduced equivalent widths to give same abundances

Spectroscopic temperature determination

Stellar parameter derivation ● Traditionally, two techniques for stellar parameter derivation – Photometric ● Use color-Teff relations to derive temperatures from photometry (note metallicity dependence) ● Use absolute magnitude to determine gravity from stellar models (requires distance)

Color-temperature-metallicity relation

Stellar parameter derivation ● Traditionally, two techniques for stellar parameter derivation – Spectroscopic – Photometric ● Unfortunately, these do not always agree! – Issues: errors in measurements, scatter in relations, applicability of LTE, errors in atomic data, inaccuracies in stellar atmospheres, etc. – Differences affect abundances at the 0.1 dex level

New technique for stellar parameters ● Attempt to use both photometric and spectroscopic information, look for single solution consistent with both ● For spectroscopic solutions, realize that not all combinations of effective temperature, surface gravity, and metallicity are consistent with stellar models ● Construct likelihood estimator: for a given set of atmospheric parameters (Teff, log g, [M/H]), calculate likelihood of observed equivalent widths, color, and absolute magnitude ● Constrain combinations of allow atmospheric parameters based on stellar evolution models – Basic underlying variables are mass, age, and chemical composition – Searching in mass is very difficult because of large dynamic range required ● Search in “equivalent evolutionary state”

Tuning atomic parameters ● Use large stellar sample to study behavior of individual lines

Chemistry results: still investigating PhotometricHybrid

Spectroscopic distances ● Can use full spectroscopic fit, constrained by possible stellar models, to derive distances and extinctions

Future ● Work – Add more elements – neutron capture – Chemistry analysis – SFH analysis – Read & write!

APOGEE: APO Galactic Evolution Experiment ● One of 3(4) main components of SDSS-III project ● Other similar projects? – HERMES – LAMOST HiRES?